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#
# This file is part of TEN Framework, an open source project.
# Licensed under the Apache License, Version 2.0.
# See the LICENSE file for more information.
#
from ctypes import c_int, c_int32, c_float, c_size_t, CDLL, c_void_p, POINTER
import numpy as np
import os
class TenVad:
def __init__(self, hop_size: int = 256, threshold: float = 0.5):
self.hop_size = hop_size
self.threshold = threshold
if os.path.exists(
os.path.join(
os.path.dirname(os.path.relpath(__file__)),
"../lib/Linux/x64/libten_vad.so",
)
):
self.vad_library = CDLL(
os.path.join(
os.path.dirname(os.path.relpath(__file__)),
"../lib/Linux/x64/libten_vad.so",
)
)
else:
self.vad_library = CDLL(
os.path.join(
os.path.dirname(
os.path.relpath(__file__)),
"./ten_vad_library/libten_vad.so",
)
)
self.vad_handler = c_void_p(0)
self.out_probability = c_float()
self.out_flags = c_int32()
self.vad_library.ten_vad_create.argtypes = [
POINTER(c_void_p),
c_size_t,
c_float,
]
self.vad_library.ten_vad_create.restype = c_int
self.vad_library.ten_vad_destroy.argtypes = [POINTER(c_void_p)]
self.vad_library.ten_vad_destroy.restype = c_int
self.vad_library.ten_vad_process.argtypes = [
c_void_p,
c_void_p,
c_size_t,
POINTER(c_float),
POINTER(c_int32),
]
self.vad_library.ten_vad_process.restype = c_int
self.create_and_init_handler()
def create_and_init_handler(self):
assert (
self.vad_library.ten_vad_create(
POINTER(c_void_p)(self.vad_handler),
c_size_t(self.hop_size),
c_float(self.threshold),
)
== 0
), "[TEN VAD]: create handler failure!"
def __del__(self):
assert (
self.vad_library.ten_vad_destroy(
POINTER(c_void_p)(self.vad_handler)
)
== 0
), "[TEN VAD]: destroy handler failure!"
def get_input_data(self, audio_data: np.ndarray):
audio_data = np.squeeze(audio_data)
assert (
len(audio_data.shape) == 1
and audio_data.shape[0] == self.hop_size
), "[TEN VAD]: audio data shape should be [%d]" % (
self.hop_size
)
assert (
type(audio_data[0]) == np.int16
), "[TEN VAD]: audio data type error, must be int16"
data_pointer = audio_data.__array_interface__["data"][0]
return c_void_p(data_pointer)
def process(self, audio_data: np.ndarray):
input_pointer = self.get_input_data(audio_data)
self.vad_library.ten_vad_process(
self.vad_handler,
input_pointer,
c_size_t(self.hop_size),
POINTER(c_float)(self.out_probability),
POINTER(c_int32)(self.out_flags),
)
return self.out_probability.value, self.out_flags.value
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